Main goal of web recommendation system is to study how user behavior on a website can be predicted by analyzing web log data which contain the visited web pages. Many researches of the web recommendation system have been studied. To construct web recommendation system, web mining is needed. Especially, web usage analysis of web mining is a tool for recommendation model. In this paper, we propose web recommendation system using grid based support vector machines for improvement of web recommendation system. To verify the performance of our system, we make experiments using the data set from our web server.

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

Fingerprints have been widely used in the biometric authentication because of its performance, uniqueness and universality. Lately, the speed of identification has become a very important aspect in the fingerprint-based security applications. Also, the reliability still remains the main issue in the fingerprint identification. A fast and reliable fingerprint matching algorithm based on the process of the `self-nonself` discrimination in the biological immune system was proposed. The proposed algorithm is organized by two-matching stages. The 1st matching stage utilized the self-space and MHC detector string set that are generated from the information of the minutiae and the values of the directional field. The 2nd matching stage was made based on the local-structure of the minutiae. The proposed matching algorithm reduces matching time while maintaining the reliability of the matching algorithm.

The notion of ideals in subtraction algebras and characterizations of ideals introduced by Y.B.Jun et al. [?]. Using this idea, we consider the fuzzification of an ideal of a subtraction algebra. In this paper, we define the concept of a fuzzy ideal of a subtraction algebra and study characterizations of a fuzzy ideal. We give some conditions to show that a fuzzy set in a subtraction algebra is a fuzzy ideal of a subtraction algebra. We investigate the generalization of some properties of a fuzzy ideal of a subtraction algebra.

The control of electrical appliances residing in the home network can be accomplished via Internet with the UPnP expansion without modifying an existing UPnP. In this paper, we propose the Internet Gateway that consists of an UPnP IGD(Internet Gateway Device) DCP(Device Control Protocol) and an UPnP Bridge as a system to control electrical appliances of home network. UPnP IGD DCP is to enable the configurable initiation and sharing of Internet connections as well as assuring advanced connection-management features and management of host configuration service. It also supports transparent Internet access by non-UPnP-certified devices. UPnP Bridge searches for local home network devices by sending control messages, while control point of UPnP Bridge looks up devices of interest on the Internet, subsequently furnishing the inter-networking controlling among devices which belong to different home network systems. With our approach, devices on one home network can control home electrical appliances on the other home network via Internet through IGD DCP with control commands of UPnP.

Experimental software data capturing the essence of software projects (expressed e.g., in terms of their complexity and development time) have been a subject of intensive modeling. In this study, we introduce a new category of Hybrid Fuzzy Neural Networks (gHFNN) and discuss their comprehensive design methodology. The gHFNN architecture results from highly synergistic linkages between Fuzzy Neural Networks (FNN) and Polynomial Neural Networks (PNN). We develop a rule-based model consisting of a number of "if-then" statements whose antecedents are formed in the input space and linked with the consequents (conclusion pats) formed in the output space. In this framework, FNNs contribute to the formation of the premise part of the overall network structure of the gHFNN. The consequences of the rules are designed with the aid of genetically endowed PNNs. The experiments reported in this study deal with well-known software data such as the NASA dataset. In comparison with the previously discussed approaches, the proposed self-organizing networks are more accurate and yield significant generalization abilities.

This paper presents an algorithm which extends the rapidly-exploring random tree (RRT) framework to deal with change of the task environments. This algorithm called the Retrieval RRT Strategy (RRS) combines a support vector machine (SVM) and RRT and plans the robot motion in the presence of the change of the surrounding environment. This algorithm consists of two levels. At the first level, the SVM is built and selects a proper path from the bank of RRTs for a given environment. At the second level, a real path is planned by the RRT planners for the: given environment. The suggested method is applied to the control of , a commercial 6 DOF robot manipulator, and its feasibility and efficiency are demonstrated via the cosimulatation of .

This paper proposes a new watermarking scheme in which a logo watermark is embedded into the discrete wavelet transform (DWT) domain of the original image using exact radial basis function neural networks (RBF). RBF will learn the characteristics of the image, and then watermark is embedded and extracted by the trained RBF. A watermark is added to the coefficients at the low frequency band of the DWT of an image and a watermark is embedded into the DWT domain using the trained RBF. The trained RBF also used in watermark extracting process. Experimental results show that the proposed method has good imperceptibility and high robustness to common image processing attacks.

This paper deals with implementing a steganography based multi-modal biometric system. For this purpose, we construct a multi-biometrics system based on the face and iris recognition. Here, the feature vector of iris pattern is hidden in the face image. The recognition system is designed by the fuzzy-based Linear Discriminant Analysis(LDA), which is an expanded approach of the LDA method combined by the theory of fuzzy sets. Furthermore, we present a watermarking method that can embed iris information into face images. Finally, we show the advantages of the proposed watermarking scheme by computing the ROC curves and make some comparisons recognition rates of watermarked face images with those of original ones. From various experiments, we found that our proposed scheme could be used for establishing efficient and secure multi-modal biometric systems.

As the technology developed, the system is being developed as the structure that is adapted to the intelligent environment. Therefore, the existing situation information system couldn`t provide satisfactory service to the user as it provides service only by the information which it received from the sensor. This paper analyzed the problems of the existing user intention awareness system and suggested user intention awareness system to provide a stable and efficient service that fits to the intention of the user compensating this. This paper has collected the behavior data based on the scenario of the sequential behavior course of the user that occurs at breakfast time in the kitchen which is the home domain environment thai is closely related to our lives. This scenario course also showed the flow that the goal intentional user intention awareness system acted that it suggested, and showed the sequential course processing the user behavior data by tables and charts.